A new approach to change vector analysis using distance and similarity measures

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.creatorCarvalho Júnior, Osmar Abílio de-
Autor(es): dc.creatorGuimarães, Renato Fontes-
Autor(es): dc.creatorGillespie, Alan R.-
Autor(es): dc.creatorSilva, Nilton Correia da-
Autor(es): dc.creatorGomes, Roberto Arnaldo Trancoso-
Data de aceite: dc.date.accessioned2021-10-14T17:38:38Z-
Data de disponibilização: dc.date.available2021-10-14T17:38:38Z-
Data de envio: dc.date.issued2012-05-15-
Data de envio: dc.date.issued2012-05-15-
Data de envio: dc.date.issued2011-11-
Fonte completa do material: dc.identifierhttp://repositorio.unb.br/handle/10482/10472-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/612803-
Descrição: dc.descriptionThe need to monitor the Earth’s surface over a range of spatial and temporal scales is fundamental in ecosystems planning and management. Change-Vector Analysis (CVA) is a bi-temporal method of change detection that considers the magnitude and direction of change vector. However, many multispectral applications do not make use of the direction component. The procedure most used to calculate the direction component using multiband data is the direction cosine, but the number of output direction cosine images is equal to the number of original bands and has a complex interpretation. This paper proposes a new approach to calculate the spectral direction of change, using the Spectral Angle Mapper and Spectral Correlation Mapper spectral-similarity measures. The chief advantage of this approach is that it generates a single image of change information insensitive to illumination variation. In this paper the magnitude component of the spectral similarity was calculated in two ways: as the standard Euclidean distance and as the Mahalanobis distance. In this test the best magnitude measure was the Euclidean distance and the best similarity measure was Spectral Angle Mapper. The results show that the distance and similarity measures are complementary and need to be applied together.-
Formato: dc.formatapplication/pdf-
Publicador: dc.publisherMDPI - Open Access Publishing-
Direitos: dc.rightsAcesso Aberto-
Direitos: dc.rightsAll articles published by MDPI are made available under an open access license worldwide immediately. This means: everyone has free and unlimited access to the full-text of all articles published in MDPI journals, and everyone is free to re-use the published material given proper accreditation/citation of the original publication open access publication is supported by authors' institutes or research funding agency by payment of a comparatively low Article Processing Charge (APC) for accepted articles. Fonte: http://www.mdpi.com/about/openaccess/. Acesso em: 15 maio 2012-
Palavras-chave: dc.subjectAnálise espectral-
Palavras-chave: dc.subjectGeometria euclidiana-
Título: dc.titleA new approach to change vector analysis using distance and similarity measures-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional – UNB

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